In this interview, we discuss digital transformation with Jin Watanabe, a consultant and solution architect specialising in leveraging automation technologies like AI, Business Intelligence, and Robotic Process Automation (RPA). He shares valuable insights on the impact of groundbreaking technology on the workplace. Alongside his work in developing innovative AI agents, Watanabe acts as a technical advisor for start-ups, emphasising the critical role of employee motivation and effective communication in fostering a culture of innovation. He envisions a future where people and automation technologies, such as AI, coexist harmoniously, empowering everyone to pursue their dreams.
Key Takeaways
- How will AI transform the way employees work? AI will automate repetitive tasks, creating an environment where employees can focus on high-value, creative work, ultimately enhancing job satisfaction and productivity.
- What is the most significant barrier to AI adoption in companies? The primary barriers are scattered internal data not ready for AI utilisation and the lack of a long-term vision for AI adoption. Successful implementation requires a long-term vision, the development of a data infrastructure, and an improvement in employee AI literacy, including their perspective on the technology.
- How can leaders promote AI adoption and alleviate employee anxiety? It is crucial to communicate a clear vision for “how we will utilise AI,” release prototypes early, and actively involve employees in the improvement process to foster a sense of ownership over AI among all staff members.
- Will AI take human jobs, and how should employees prepare? In the future, AI will likely handle almost all simple tasks. However, AI itself has no motivation. In the AI era, individuals can pursue what they truly want to do, and if they see AI as a reliable partner to achieve that, there has never been a more exciting time.
- What can leaders do right now to embrace technology? Leaders should start by actively using AI themselves. They must communicate a clear vision for its use and implement effective measures, such as incorporating AI utilisation into evaluation metrics.
- How will the relationship between employees and AI evolve in the next five years? From a talent perspective, AI will dramatically improve the accuracy of matching business professionals with companies. As AI takes over routine work, the value of simple “work speed” will decrease relatively, making individual motivation and creativity essential for talent.
The Origin of the Mission: To Eliminate Tedious Work
I want to inquire about your professional mission to "eliminate unfulfilling work." Can you share the experiences that inspired you to develop this mission?
Absolutely. My time as a graduate at a major manufacturing company was eye-opening. I joined the software development department and was taken aback by what I encountered. While the organisation engaged in groundbreaking projects, I noticed many colleagues were caught up in mundane tasks. They spent their days scheduling meetings, filing expense reports, creating client invoices, and circulating documents for approval. Having studied physics at university and delved into AI during graduate school, I had high expectations about the kind of work professionals would be doing. Witnessing many individuals in a large corporation bogged down by routine activities shocked me.
One significant event involved a colleague from the hardware design team. He was tasked with developing a new product prototype, which required him to sift through an extensive Excel parts list containing tens of thousands of rows to determine how many components were necessary. As a result, he found himself working late every night. Since I had some experience writing Excel macros, I used my lunch breaks to create a macro to automate this painstaking process. What once took him hours was completed in just a few minutes. I still recall how thrilled he was—not just because he was relieved of the extra hours, but also because he could now devote his time to more meaningful tasks he was passionate about, like the actual design work. This experience opened my eyes to the incredible impact of automation; it creates an environment where everyone can concentrate on what they genuinely want to pursue.
That was around 2017, just as RPA (Robotic Process Automation) emerged and “work-style reform” became a significant trend in Japan. Then, I decided to pursue a path in automation seriously, so I moved to a consulting firm with a specialised department for RPA and DX promotion. The term DX was still new, but as I worked on automating processes for various clients through trial and error, I often received direct words of gratitude like, “Thanks to you, I can go home earlier.” That direct feedback made me incredibly happy and remains a core experience for me to this day.
A Leader's Perspective: Overcoming the Hurdles of AI Adoption
Those early experiences with automation shaped your origin story. The time that technology frees up allows individuals to leave work early, enabling them to treasure moments with family or personal time, while also pursuing work they are truly passionate about. "Time" stands out as a central theme.
From the viewpoint of companies and their leaders, the effort and costs associated with implementation are major concerns. However, understanding the tangible benefits without putting them to the test can be quite challenging, making that initial leap feel like a daunting task. What guidance can you share to help overcome this initial hurdle?
A company’s approach largely hinges on its vision, particularly how well it can adopt a medium-to-long-term perspective. If the primary focus is short-term gains, introducing new automation solutions or leveraging AI can significantly disrupt existing workflows. This shift can come with challenges, such as the initial costs of implementation and the need to adapt to new processes. For many, sticking with familiar methods is often easier than embracing drastic changes. This phenomenon isn’t unique to AI; it mirrors our collective experience when smartphones first entered the scene. Despite the promises of greater convenience, many found them daunting at first. However, given the shrinking workforce and the rapid advancement of AI, it’s essential to tackle that initial discomfort, especially when viewed through a long-term lens.
The impact of AI adoption isn’t always felt right away. For most companies, the groundwork necessary for immediate benefits, such as data preparation and employee literacy, isn’t in place yet. This journey is not just about achieving quick, easily digestible results; it is about creating a solid foundation for meaningful and sustainable outcomes in the long term. Think of it more as a strategic investment. This can be a tough pill to swallow for companies that lack the necessary stamina or resources. While noticeable changes may not occur in six months or even a year, a significant gap could emerge after three to five years. With the rapid evolution of AI expected to accelerate, companies that delay their efforts might find their business models outdated before they even realise it. It is essential to view this as more than just a one-time efficiency boost; it is foundational work paving the way for a true AI-driven future.
Once that foundation is built, catching up with new technologies, including further advances in AI, and reaping the benefits will become extremely fast. This means that in the age of AI, it is necessary to transform into an “AI-ready” company in stages.
The biggest problem in AI adoption is when company data is scattered or remains primarily in analogue, paper-based formats and is not organised correctly. No matter how much the performance of AI improves in the future, its actual value cannot be unlocked if the necessary data is unavailable. In reality, a company that has neglected digitalisation and DX will likely find that even if it suddenly introduces an AI solution or hires brilliant AI engineers, the project will fail because it cannot access the required data. The companies benefiting most from AI have painstakingly engaged in DX, including digitalisation, through trial and error.
While immediate and noticeable results from adopting AI aren’t guaranteed, how an organisation strategically frames its AI use for the medium- to long-term will be crucial for all businesses moving forward. Implementing AI often entails significant costs and transformative changes, which inherently come with risks. Conversely, choosing not to embrace AI now also carries risks as we enter the AI-driven future. This situation presents a complex challenge, as there isn’t a definitive answer, and it truly tests leaders’ visions regarding technology.
The results of AI adoption are not always immediate. Instead, it is more akin to an investment in a company's medium-to-long-term growth. To achieve true automation, it is necessary to have well-organised data that AI can utilise, and it is also crucial to foster AI literacy among employees. Right now, leaders' visions of technology are truly being tested.
AI Adoption and Adaptation: From Employee Anxiety to Assurance
It seems challenging for companies that need to prioritise short-term results to understand and execute on that long-term vision. A gap inevitably forms with the perspective on the ground: "But there are clear results right in front of us." There is definite stress on the front lines when AI is introduced. And as you mentioned, there's a need to cultivate IT literacy among employees. In your experience, how have you tackled this challenge of improving employee IT literacy?
From the employees’ point of view, the biggest question is, “Will this make my job easier?” A common mistake is to impose instructions from the outset in a one-sided manner, such as, “Data is important, so if you input it into the system correctly, we can use AI.” From the perspective of the front-line staff, if they are to change their current methods, they won’t be motivated to change their work if there isn’t a commensurate return for the effort involved. Therefore, regardless of whether it’s an AI implementation, what I prioritise most when introducing a new solution is to create a prototype or demo early and have the business users try it and experience it firsthand. By letting them get a real feel for it and think, “I’d want to use this,” we receive feedback from their perspective and collaboratively create a state where all stakeholders can see the final goal.
What I prioritise most is creating a prototype or demo at an early stage and having users try it first. By making them feel, "I'd want to use this," we create a state where the final goal is visible.
A great example is the creation of a business intelligence (BI) dashboard. What used to take hours of manual data compilation can now be visualised instantly, allowing necessary information to be shared with stakeholders at any time. We ensure that they experience this “return” firsthand. If an error occurs due to incorrect data entry, they can understand the cause and effect: “Ah, it’s not displaying correctly because I didn’t input that properly.” Establishing this understanding of “return” is crucial.
I’ve noticed a shared trait among exceptional leaders driving digital transformation. Instead of striving for perfection before a release—an approach typical of the past waterfall development model—they embrace a mindset of, “Let’s start with a prototype and involve the front-line teams from the get-go.”
This method encourages team members to take part in the project, fostering a sense of collaboration and ownership. Rather than having systems departments dictate, “We’ve built this, so please use it,” engaging front-line teams early in the development process and incorporating their feedback allows us to create something more substantial. This sense of ownership boosts development efficiency and quality, resulting in better adoption post-release and ongoing improvement efforts.
Those on the front lines have the best grasp of their work. The key isn’t about top-down imposition; it’s about merging on-the-ground realities with executives’ visions through effective communication. To achieve this, it’s vital to avoid getting bogged down in abstract discussions and involve stakeholders early by presenting them with tangible solutions.
This approach significantly improves the environment for boosting productivity, eliminating wasteful tasks, and focusing on higher-value work
Shifting gears a bit, I want to highlight something that I believe is crucial at this moment, not only from a front-line perspective but also for management: the “visualisations” of relevant information. Many companies still operate under a culture where documents are created solely for reporting. Data is pulled from various systems, compiled, and then submitted as a report to management. This process can be a significant source of stress, not just for the person putting the document together but also for the manager who requested it, who often deals with delays or has to ask for revisions.
In one automation project I worked on, I partnered with a client to develop a dashboard that visualised the project’s overall progress and ROI. Before this, creating quarterly reports was tedious, and management frequently struggled to get a real-time view of developments. By implementing this dashboard, we significantly lightened the team’s workload and allowed management to check the project’s status anytime. Consequently, we eliminated regular progress report meetings and opted for ad-hoc discussions when issues arose, allowing us to have more focused conversations with relevant stakeholders. This adjustment greatly enhanced the speed and quality of the project’s improvement cycle.
By visualising the necessary information and fostering transparency, management is no longer burdened with the question of “What’s the current situation?” or dependent on requesting report documents. I spent a lot of time early in my career creating reports just for the sake of reporting, but it is essential, both from the front-line and management perspectives, to reduce this type of work. Instead of meetings that serve only to relay information, we can focus on discussing “What should we do next?” based on that data.
We can even take it further by leveraging AI to derive insights. This enables us to conduct analyses that previously would have been outsourced to consulting firms. Now we can address, “Here’s what’s happening, and here are the recommendations based on AI analysis,” all in-house and without delay. This means the current situation is always on display, allowing stakeholders to engage in discussions around AI’s suggestions for improvements, which leads to more time spent on high-quality debates. In this way, we can redirect the time once spent on mundane tasks toward more value-added work.
Visualising data eliminates "meetings for the sake of reporting." Then, using that data and AI insights as a base, you focus the discussion on action: "What should we do next?"
In an era when AI and technology are becoming commonplace, what skill sets and mindsets should employees have, and what approach can leaders take to cultivate them?
In today’s AI-driven landscape, leaders must communicate clearly: “The definition of excellent talent has evolved.” Skills that were once highly valued, such as logical thinking and the ability to process assigned tasks quickly, are now areas where AI excels, resulting in diminished added value for those abilities. Conversely, there is a growing appreciation for individuals who can generate original ideas from scratch, a “zero-to-one” approach, even if those ideas are not fully polished. There is also value in those who can offer unconventional perspectives on issues. The capacity to ask innovative questions is becoming more vital than merely providing the correct answers. We are transitioning into a time when behaviours that might have once been discouraged for new graduates are now seen as beneficial. Without clear messaging from leadership, however, employees may feel uncertain about expectations, wondering what they need to achieve now and if they still meet standards. This uncertainty can stifle proactivity. Leaders can foster greater employee engagement and create a more conducive work environment by explicitly defining the organisation’s expectations regarding technologies like AI.
The second point concerns organisational structure. I frequently collaborate with large clients, and maintaining a sense of ownership among employees in big corporations is always a challenge. Despite efforts to flatten the organisational hierarchy, teams are essential for business operations, and the nature of large organisations tends to lead to expanded structures.
However, in this age of AI, we can expect significant changes in this framework. As AI increasingly becomes a primary workforce, the traditional hierarchical model filled with people will transform. Human roles will shift towards higher-level tasks such as planning and management, while AI will take on the execution layer.
This shift does not imply that AI will replace human workers; it suggests that organisations can maintain their workforce levels while expanding the number of teams. A future objective will be to cultivate small, elite teams composed of just a few individuals supported by multiple powerful AIs. In such a scenario, everyone will have the opportunity to step into a leadership role.
It's natural for people to question, "Can we implement this in our company? Will it be effective?" However, immediately rolling out a company-wide policy is tough. Is it more practical to start by testing it within a specific team or department?
That’s a solid approach. Start with a small team and then gradually implement the successful model across the organisation. Employees can develop a strong sense of ownership by piloting new working methods as they shift from the traditional people-based pyramid to a more AI-driven structure. Rather than merely following top-down directives, they will have a valuable partner in AI, empowering them to carve their paths and drive projects forward. This should make work increasingly enjoyable for everyone involved.
The Future of AI and Work: A Human-Centric Perspective
The evolution of AI is relentless. At the same time, there's a long-discussed concern: the fear that the rise of AI will eliminate the jobs people have traditionally done and their "place" in the workplace. What are your thoughts on this?
In today’s age of AI, I firmly believe that people should embrace a more “wilful” (wagamama) approach and genuinely pursue what they desire. Historically, especially within Japanese organisations, being viewed as “talented” meant executing assigned tasks swiftly and accurately. Suppressing one’s individuality was often regarded as a commendable trait. However, as we step into a future where AI handles many tasks, we must shift away from this restrictive mindset we have cultivated over the years.
Throughout our education and professional journeys, we have been conditioned to read the room and stifle our true desires, as if we shouldn’t pursue what genuinely excites us. It is time for a change. I have noticed a growing sense of “willfulness” within myself, not in a selfish way, but as a commitment to being true to my wishes. With AI as a reliable ally at our fingertips, my list of “I want to do this, I want to do that” keeps expanding.
When I share this perspective, I often hear people say, “I don’t have anything I want to do in particular.” However, after digging a little deeper, it becomes clear they have aspirations; they have just given up on them, thinking, “I can’t do it,” or “I shouldn’t do it.” This perspective is such a loss, especially in the age of AI, because it highlights a crucial distinction between humans and machines: unlike us, AI lacks motivation.
Motivation, our internal drive to pursue desires, is the distinctive value that belongs solely to humans. Holding on to that intrinsic motivation can be seen as “wilful.” With that in place, we can harness AI as a powerful ally to turn our aspirations into reality.
The fear surrounding job security in the face of AI often stems from the belief that “my job is to process tasks.” However, if we shift our perspective to “I will leverage AI to explore challenges I previously thought were beyond my reach, to pursue what I genuinely want,” AI transforms into an incredibly supportive partner. This change in mindset is fundamental. In this AI era, we may return to a state of pure childhood wonder and curiosity. When viewed through this lens, there has never been a more exhilarating time to be alive.
Driving DX: The Future of AI in Southeast Asia
Let's shift our attention to Southeast Asia, specifically Singapore, where we engage in business. Since you relocated to Singapore in 2024, your experience there has been relatively short. However, I'd love to hear your insights on the challenges Japanese companies face in this region concerning digital transformation and your thoughts on the prospects and expectations moving forward.
Certainly! When discussing the ability to transcend national borders, I see AI playing a vital role as a “lubricant” that fosters cooperation among countries. It can serve as a bridge, facilitating communication through language translation and enhancing mutual understanding of diverse cultures, histories, and values. As a result, advancements in this area will surely pick up speed. This is particularly true for individuals coming to Japan from abroad. Language and cultural barriers posed significant challenges in the past, but AI is set to break down these obstacles.
For instance, a common challenge in the manufacturing industry is setting up factories overseas and hiring local staff, only to face issues with employee retention. This can be hard to identify from Japan during the planning phase. However, with the assistance of AI, businesses can gain valuable insights on what to keep in mind when operating in a specific region, presented in a clear and detailed manner that considers local customs, culture, history, and values. While this information is only a starting point, it can provide crucial primary data that would have previously taken considerable time and resources.
On the flip side, when Southeast Asian entrepreneurs look to enter the Japanese market, AI can significantly streamline their preliminary research and communication with local partners, reducing the extensive effort that was once necessary and allowing them to concentrate on more pressing initiatives. I am excited about the prospect of AI serving as a helpful lubricant between nations, greatly enhancing cross-border projects and fostering collaborative relationships.
Reflecting on my own experiences, before the advent of AI, I worked on an offshore development project with engineers from India. That experience highlighted the challenges we faced in communication, frequent misunderstandings, and difficulties with coordinating responses and meetings. Additionally, we encountered cultural differences. In India, it is common for individuals to switch jobs frequently to secure salary increases, sometimes leading to distractions about future career moves while still on the job. As the saying goes, what is common sense in Japan might seem nonsensical abroad. AI has the potential to bridge these cultural and value gaps effectively. Thinking from both perspectives can significantly enhance communication between diverse teams.
A Leader's Guide: Empowerment Fostered by AI
Through our conversation today, I gained a clearer understanding of the positive effects that technology and digital transformation (DX) can have. If a leader were to take one initial step, perhaps as soon as tomorrow, to embrace technology and encourage more high-value work, what would be the best place to begin?
Leaders need to gain hands-on experience with AI before diving in. Various tools, such as ChatGPT, Claude, and Gemini, are available; it is crucial to experiment with them. However, beyond this exploration, developing a personal “philosophy” regarding AI usage is vital. There is no one-size-fits-all approach to integrating AI, so companies must thoroughly discuss “how we will utilise AI.” Suppose a tool like ChatGPT is introduced without these conversations or a guiding policy. In that case, employees may feel lost regarding how extensively they should engage with AI and the direction in which to steer their efforts.
I found it particularly intriguing that a well-known international company has included a metric in its employee evaluations for “how much AI has been utilised.” While it varies by industry, especially in white-collar environments, an employee who claims “I don’t use AI much” could be viewed as underperforming in this AI era, essentially a sign of low productivity. Incorporating AI utilisation into evaluation criteria sends a clear message: “Using AI is part of our company policy.” This motivates employees to adopt AI and reassures those passionate about it that they can pursue their interests without hesitation. Moreover, this creates a virtuous cycle where leaders gain insights from performance reviews, such as feedback on practical AI usage, which can then be disseminated throughout the organisation.
When speaking with friends who are employees, I often hear uncertainty about the extent to which they can use AI or whether it is even encouraged at their companies. So, incorporating AI utilisation into evaluation metrics is a mere call to action and a clear directive.
As another example, some companies have implemented a system for new business proposals that asks, “Have you thoroughly considered whether AI can perform this task?” Typically, when proposing a new initiative, one outlines the human resources needed to launch it. In doing so, they must justify “why this task requires human intervention instead of AI.” This approach compels proposers to first reflect on whether AI could handle the task and seek human resources only if they conclude it is challenging for AI. I believe this ongoing questioning of “Could AI do this?” can serve as valuable training for employees, enhancing their understanding of AI and boosting their literacy in this new era. Creating effective “systems” will ultimately motivate the organisation and its employees to embrace AI.
That's a valid point. Leaders must do more than experiment with AI or declare, "Let's incorporate AI." They need to integrate it firmly into the organisation as a fundamental system.
It’s not enough for leadership to make calls to action through common messages or videos. When a company establishes a concrete system, such as stating, “We will include this in our evaluation process,” it conveys its serious intent to employees.
One effective approach could be to set up a working group dedicated to ongoing discussions about AI utilisation within the organisation. For the evaluation system, in addition to assessing individual usage, we might include criteria like, “Did you share your new insights and knowledge with the team?” Given the rapid evolution of AI, it has become nearly impossible for anyone to keep up with everything on their own. This underscores the necessity for a collective effort. By evaluating individual usage and the contribution to the team’s overall productivity through knowledge sharing, we can create positive momentum and foster a synergistic learning environment.
Many factors influence how individuals feel about embracing new challenges, but it ultimately falls on leaders to cultivate that motivation and awareness, regardless of skill levels.
The Impact of People and Automation: The 5-Year Outlook for Recruitment and Talent
I'm interested in discussing the connection between "working people" and "automation." This relationship will evolve, but how might it change over the next five years?
First, in the world of recruitment and job seeking, AI is set to significantly enhance matching accuracy for job seekers and companies searching for talent. With this improvement, individuals must express their career aspirations clearly and authentically, almost as if they are being “willful” about their goals. If you hold back and rely on generic, cookie-cutter phrases to appeal to everyone, the AI will struggle to grasp your true intentions. Conversely, if you clearly state, “This is what I want to do,” even if your previous options were limited, you will find that the pool of potential matches expands considerably, allowing AI to pinpoint the best candidates for you.
Similarly, when companies provide vague job descriptions or unclear expectations, it becomes challenging for AI to understand their real intent. Clear communication is essential from both sides. With a broader range of options available, each party should confidently articulate their goals, allowing AI to handle the matching process.
As I have mentioned, while productivity is set to soar with AI, motivation remains a distinct issue because AI lacks intrinsic motivation. My vision for automation is to empower individuals who are full of ambition but may lack the resources to initiate new projects. For instance, by providing the technology of automation and AI to those who have the drive but are held back by financial constraints, we can significantly expand the capabilities of both individuals and organisations. I envisage a future where everyone feels excited to pursue their true passions.
On the other hand, no matter how quickly someone can complete tasks or how intelligent they are, the value of a person who lacks a strong motivation, which is “this is what I want to do,” may diminish. Interestingly, this shift in value is quite positive. The real challenge in the forthcoming AI era is to break away from the traditional perspective of measuring value based on task efficiency and accuracy, and instead embrace a more “willful” mindset similar to that of a child. When you have a genuine drive to pursue something and articulate that desire, AI will support you.
I initially set out on a path focused on automation. Still, my mission has evolved towards empowering individuals and organisations to achieve a state where they are truly engaged in activities that matter to them. Routine yet essential tasks can be delegated to AI, and we are approaching an era where it is acceptable but vital to chase what you genuinely want to do. Perhaps that is the only pursuit that holds real value.
The distinction between "fast workers" and "slow workers" may soon fade. With everyone able to achieve a reliable level of speed through AI, the feelings of superiority or inferiority tied to work pace will likely diminish, making it no longer a valid point of differentiation.
Yes, that concept is destined to fade away. The human qualities of charm, such as motivation, creativity, and uniqueness, will be scrutinised now. We are stepping into a time when the meaning of an “excellent person” is shifting dramatically.
As an engineer, I once considered programming skills to be crucial. However, I can now delegate many tasks to AI, including programming and testing. This lets me realise my creative ideas quickly while focusing on business domains and strategic planning. As a result, I can manage more than five projects at once. What was merely a dream five or ten years ago is a vibrant reality, and I could not be happier.
We are moving into an era where determination is encouraged, and you can pursue your passions. I would be thrilled to see a future where everyone, especially those stuck in monotonous jobs and the younger generation, can wholeheartedly enjoy chasing what truly fulfils them. I am committed to making the most of this technology called AI to help bring my dreams and those of others to life.
I genuinely believe we've stepped into a time where being "willful" is not just accepted, but encouraged. It's an age where anyone can pursue their passions and achieve their goals. The aspiration is to create a world where everyone, from those stuck in monotonous jobs to the younger generations, can wholeheartedly enjoy doing what they genuinely want, all thanks to the advancements in AI.
Jin Watanabe
Jin Watanabe is a consultant and solution architect specialising in business automation using AI, BI, and RPA solutions. After working as a software engineer at DENSO Corporation, he led the launch and management of Automation CoEs for numerous clients at KPMG Consulting and IBM. He graduated from Osaka University with a degree in Physics and holds a Master's degree in Information Science from the Nara Institute of Science and Technology. After becoming independent in Japan, he now serves as the representative of Autofusion Pte. Ltd. in Singapore, where he provides technical advisory services to AI ventures and supports the development and promotion of AI agents.
Jin Watanabe’s insightful perspective offers a compelling vision for the future of work as it is nurtured alongside AI. If your company seeks to transform through AI adoption and is interested in a solution proposal, please contact him at jin.watanabe@autofusion-sg.com.
Navigating the complexities of AI adoption and DX requires a strategic partnership. Good Job Creations is committed to supporting your company on this journey and connecting you with the right talent and solutions. For questions and consultations, please contact us at enquiry@goodjobcreations.com.sg.
